Carbon emissions measurement as intra-action: incentives to disclose air emissions at a Canadian university
Bibliographic record
Abstract
Purpose The purpose of this paper is to use the case of York University in Canada to analyze the connection between University Social Responsibility and voluntary disclosure. The authors examine whether the university’s voluntary air emissions disclosure is performative by exploring whether York University’s espoused commitment to its community stakeholders truly guides its incentive to disclose carbon emissions in the absence of a legal mandate. Design/methodology/approach This qualitative exploratory study uses a post-humanistic approach to build on publicly available data on key measures and metrics of air quality and carbon emissions to facilitate our understanding of representational and interventionist uses of measurement models by social actors and their basis for making voluntary disclosures. Findings York University linked the logic of capital markets with sustainability disclosures as an incentive for managing the cost of long-term debt. This paper contributes to measurement practice of sustainability disclosure by reinforcing the practice-theoretic conception of measurement that questions the independent nature of objects measured from the measurement methods and reporting tools. Practical implications The findings of this study are important to higher education administrators, regulators and policymakers, as they offer a strategic guide for the assessment of reports on an organization’s commitment to sustainability and in determining the efficacy of voluntary reporting to community stakeholders in general although they are intended for specific groups. Originality/value Using York University as an illustrative case, the authors argue that air emissions per se are not a reality that shapes decisions at the organizations; instead, the intra-action of air emissions measurement, communications and operational investments define the reality where sustainability is advanced. Specifically, the authors find that the performative effects of emissions disclosure may be associated with socially desirable outcomes in terms of social responsibility and concrete financial rewards.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".